Practitioner evaluation of a novel online integrated oral health and risk assessment tool: a practice pilot.

AIM: To report the development and evaluation of an evidence-based, online, patient assessment tool, capable of measuring oral health status, future disease risk and capitation fee guidance. METHODS: An online integrated oral health and risk assessment tool called DEPPA was developed, incorporating 1) PreViser(™) risk scores for periodontal disease, caries, non-carious tooth surface loss and oral cancer, 2) revised versions of Denplan Excel's Oral Health Score and 3) capitation fee guidance score. DEPPA was piloted by 25 dentists who provided quantitative and qualitative feedback. RESULTS: Six hundred and forty assessments were performed. There was strong agreement on the need for such a tool, that it constituted a comprehensive assessment and supported good patient communication. The validity of the system was perceived as sound and the revised capitation fee guidance broadly welcomed. While some deemed the caries risk scoring algorithm to be too sensitive, the 30% high/very high risk rating is consistent with current rates of active caries in UK adults. CONCLUSIONS: A viable online oral health and risk-assessment tool has been developed (DEPPA) that will allow dental teams to measure oral health status, future disease risk and receive ongoing guidance on capitation fee setting. The indications are that DEPPA could be a valuable audit, care planning and patient communication tool.

Thermally assisted quantum annealing of a 16-qubit problem.

Efforts to develop useful quantum computers have been blocked primarily by environmental noise. Quantum annealing is a scheme of quantum computation that is predicted to be more robust against noise, because despite the thermal environment mixing the system's state in the energy basis, the system partially retains coherence in the computational basis, and hence is able to establish well-defined eigenstates. Here we examine the environment's effect on quantum annealing using 16 qubits of a superconducting quantum processor. For a problem instance with an isolated small-gap anticrossing between the lowest two energy levels, we experimentally demonstrate that, even with annealing times eight orders of magnitude longer than the predicted single-qubit decoherence time, the probabilities of performing a successful computation are similar to those expected for a fully coherent system. Moreover, for the problem studied, we show that quantum annealing can take advantage of a thermal environment to achieve a speedup factor of up to 1,000 over a closed system.

Quantum annealing with manufactured spins.

Many interesting but practically intractable problems can be reduced to that of finding the ground state of a system of interacting spins; however, finding such a ground state remains computationally difficult. It is believed that the ground state of some naturally occurring spin systems can be effectively attained through a process called quantum annealing. If it could be harnessed, quantum annealing might improve on known methods for solving certain types of problem. However, physical investigation of quantum annealing has been largely confined to microscopic spins in condensed-matter systems. Here we use quantum annealing to find the ground state of an artificial Ising spin system comprising an array of eight superconducting flux quantum bits with programmable spin-spin couplings. We observe a clear signature of quantum annealing, distinguishable from classical thermal annealing through the temperature dependence of the time at which the system dynamics freezes. Our implementation can be configured in situ to realize a wide variety of different spin networks, each of which can be monitored as it moves towards a low-energy configuration. This programmable artificial spin network bridges the gap between the theoretical study of ideal isolated spin networks and the experimental investigation of bulk magnetic samples. Moreover, with an increased number of spins, such a system may provide a practical physical means to implement a quantum algorithm, possibly allowing more-effective approaches to solving certain classes of hard combinatorial optimization problems.